/external/tensorflow/tensorflow/contrib/data/python/ops/ |
H A D | unique.py | 58 if input_dataset.output_types not in (dtypes.int32, dtypes.int64, 69 output_types=nest.flatten( 70 sparse.as_dense_types(self.output_types, self.output_classes))) 81 def output_types(self): member in class:UniqueDataset 82 return self._input_dataset.output_types
|
H A D | error_ops.py | 69 output_types=nest.flatten( 70 sparse.as_dense_types(self.output_types, self.output_classes))) 81 def output_types(self): member in class:IgnoreErrorsDataset 82 return self._input_dataset.output_types
|
H A D | random_ops.py | 54 output_types=nest.flatten( 55 sparse.as_dense_types(self.output_types, self.output_classes))) 66 def output_types(self): member in class:RandomDataset
|
H A D | readers.py | 104 if dataset.output_types == (dtypes.string, dtypes.string): 152 def __init__(self, driver_name, data_source_name, query, output_types): 178 output_types: A tuple of `tf.DType` objects representing the types of the 188 self._output_types = output_types 193 nest.flatten(self.output_types), 206 def output_types(self): member in class:SqlDataset
|
H A D | scan_ops.py | 72 sparse.as_dense_types(input_dataset.output_types, 86 input_value = nest.pack_sequence_as(input_dataset.output_types, 155 output_types=nest.flatten( 156 sparse.as_dense_types(self.output_types, self.output_classes)), 169 def output_types(self): member in class:_ScanDataset
|
H A D | shuffle_ops.py | 69 output_types=nest.flatten( 70 sparse.as_dense_types(self.output_types, self.output_classes)), 84 def output_types(self): member in class:_ShuffleAndRepeatDataset 85 return self._input_dataset.output_types
|
H A D | grouping.py | 47 `self.output_types`) to a scalar `tf.int64` tensor. 91 def __init__(self, dataset_variant, output_types, output_shapes, 95 self._output_types = output_types 111 def output_types(self): member in class:_VariantDataset 148 sparse.as_dense_types(input_dataset.output_types, 158 nested_args = nest.pack_sequence_as(input_dataset.output_types, args) 160 nested_args, input_dataset.output_types, input_dataset.output_shapes, 184 window_dataset_variant, input_dataset.output_types, 192 self._output_types = output_dataset.output_types 208 def output_types(sel member in class:GroupByWindowDataset [all...] |
H A D | interleave_ops.py | 41 sparse.as_dense_types(input_dataset.output_types, 51 nested_args = nest.pack_sequence_as(input_dataset.output_types, args) 53 nested_args, input_dataset.output_types, input_dataset.output_shapes, 64 self._output_types = dataset.output_types 97 output_types=nest.flatten( 98 sparse.as_dense_types(self.output_types, self.output_classes)), 111 def output_types(self): member in class:ParallelInterleaveDataset 211 and types defined by `self.output_shapes` and `self.output_types`) to a
|
H A D | stats_ops.py | 165 output_types=nest.flatten( 166 sparse.as_dense_types(self.output_types, self.output_classes)), 175 def output_types(self): member in class:_StatsDataset 176 return self._input_dataset.output_types
|
H A D | batching.py | 118 tuple(nest.flatten(dataset.output_types)), 143 dataset.output_types, 229 if not isinstance(input_dataset.output_types, dtypes.DType): 232 input_dataset.output_types) 244 output_types=nest.flatten( 245 sparse.as_dense_types(self.output_types, self.output_classes))) 256 def output_types(self): member in class:DenseToSparseBatchDataset 257 return self._input_dataset.output_types 265 output_types, 271 * `dataset.output_types` mus 340 def output_types(self): member in class:_RestructuredDataset 383 def output_types(self): member in class:_MapAndBatchDataset [all...] |
/external/tensorflow/tensorflow/contrib/kafka/python/ops/ |
H A D | kafka_dataset_ops.py | 73 def output_types(self): member in class:KafkaDataset
|
/external/tensorflow/tensorflow/core/kernels/data/ |
H A D | window_dataset.cc | 23 DataTypeVector output_types, 26 output_types_(std::move(output_types)), 89 DataTypeVector output_types, 93 // the elements match the output_types and output_shapes. 94 *out_dataset = new WindowDataset(std::move(elements), std::move(output_types), 22 WindowDataset(std::vector<std::vector<Tensor>> elements, DataTypeVector output_types, std::vector<PartialTensorShape> output_shapes) argument 88 NewWindowDataset(std::vector<std::vector<Tensor>> elements, DataTypeVector output_types, std::vector<PartialTensorShape> output_shapes, DatasetBase** out_dataset) argument
|
H A D | sql_dataset_ops.cc | 35 OP_REQUIRES_OK(ctx, ctx->GetAttr("output_types", &output_types_)); 81 const string& query, const DataTypeVector& output_types, 86 output_types_(output_types), 80 Dataset(const string& driver_name, const string& data_source_name, const string& query, const DataTypeVector& output_types, const std::vector<PartialTensorShape>& output_shapes) argument
|
H A D | map_dataset_op.cc | 35 OP_REQUIRES_OK(ctx, ctx->GetAttr("output_types", &output_types_)); 63 const DataTypeVector& output_types, 69 output_types_(output_types), 60 Dataset(OpKernelContext* ctx, const DatasetBase* input, const NameAttrList& func, std::unique_ptr<CapturedFunction> captured_func, const DataTypeVector& output_types, const std::vector<PartialTensorShape>& output_shapes) argument
|
H A D | flat_map_dataset_op.cc | 36 OP_REQUIRES_OK(ctx, ctx->GetAttr("output_types", &output_types_)); 64 const DataTypeVector& output_types, 70 output_types_(output_types), 61 Dataset(OpKernelContext* ctx, const DatasetBase* input, const NameAttrList& func, std::unique_ptr<CapturedFunction> captured_func, const DataTypeVector& output_types, const std::vector<PartialTensorShape>& output_shapes) argument
|
H A D | interleave_dataset_op.cc | 37 OP_REQUIRES_OK(ctx, ctx->GetAttr("output_types", &output_types_)); 84 int64 block_length, const DataTypeVector& output_types, 92 output_types_(output_types), 81 Dataset(OpKernelContext* ctx, const DatasetBase* input, const NameAttrList& func, std::unique_ptr<CapturedFunction> captured_func, int64 cycle_length, int64 block_length, const DataTypeVector& output_types, const std::vector<PartialTensorShape>& output_shapes) argument
|
H A D | padded_batch_dataset_op.cc | 169 AttrValue output_types; variable 170 b->BuildAttrValue(output_dtypes(), &output_types); variable 178 {{"Toutput_types", output_types}, {"N", N}}, output));
|
H A D | scan_dataset_op.cc | 39 OP_REQUIRES_OK(ctx, ctx->GetAttr("output_types", &output_types_)); 78 const DataTypeVector& output_types, 86 output_types_(output_types), 74 Dataset(OpKernelContext* ctx, const DatasetBase* input, const NameAttrList& func, std::vector<Tensor> initial_state, std::unique_ptr<CapturedFunction> captured_func, const DataTypeVector& state_types, const DataTypeVector& output_types, const std::vector<PartialTensorShape>& output_shapes) argument
|
/external/tensorflow/tensorflow/python/data/ops/ |
H A D | readers.py | 72 def output_types(self): member in class:TextLineDataset 117 def output_types(self): member in class:TFRecordDataset 171 def output_types(self): member in class:FixedLengthRecordDataset
|
H A D | iterator_ops.py | 56 def __init__(self, iterator_resource, initializer, output_types, 69 output_types: A nested structure of `tf.DType` objects corresponding to 80 self._output_types = output_types 87 def from_structure(output_types, 137 output_types: A nested structure of `tf.DType` objects corresponding to 153 TypeError: If the structures of `output_shapes` and `output_types` are 156 output_types = nest.map_structure(dtypes.as_dtype, output_types) 159 lambda _: tensor_shape.TensorShape(None), output_types) 162 output_types, tensor_shap 407 def output_types(self): member in class:Iterator [all...] |
/external/tensorflow/tensorflow/contrib/training/python/training/ |
H A D | tensor_queue_dataset.py | 61 padding_values, input_dataset.output_types) 93 def output_types(self): member in class:_PrependFromQueueAndPaddedBatchDataset 95 return (dtypes.variant, self._input_dataset.output_types) 147 incoming dataset's `output_types`. 150 `output_types`. If not provided, the incoming dataset's `output_shapes` 191 `dataset.output_types[1]` and `dataset.output_shapes[1]` (the non-queue
|
/external/tensorflow/tensorflow/core/kernels/data/sql/ |
H A D | sqlite_query_connection.cc | 33 const DataTypeVector& output_types) { 41 output_types_ = output_types; 76 "elements in output_types (%zu).", 31 Open(const string& data_source_name, const string& query, const DataTypeVector& output_types) argument
|
/external/tensorflow/tensorflow/contrib/eager/python/ |
H A D | datasets.py | 80 self._output_types = dataset.output_types 89 output_types=self._flat_output_types, 140 output_types=self._flat_output_types) 152 output_types=self._flat_output_types, 190 def output_types(self): member in class:Iterator
|
/external/tensorflow/tensorflow/core/kernels/hexagon/ |
H A D | graph_transfer_utils.cc | 133 DataTypeVector output_types; local 140 output_types.push_back(tst->first); 152 .Attr("Toutputs", output_types)
|
/external/tensorflow/tensorflow/tools/graph_transforms/ |
H A D | insert_logging.cc | 113 DataTypeVector output_types; local 114 TF_RETURN_IF_ERROR(GetInOutTypes(node, &input_types, &output_types)); 130 SetNodeAttr("T", output_types[0], print_node); 134 SetNodeAttr("U", output_types, print_node);
|